scholarly journals Genomic diversification of long polynucleotide fragments is a signature of emerging SARS-CoV-2 variants of concern

2021 ◽  
Author(s):  
Karthik Murugadoss ◽  
Michiel JM Niesen ◽  
Bharathwaj Raghunathan ◽  
Patrick J Lenehan ◽  
Pritha Ghosh ◽  
...  
Keyword(s):  
Viral Evolution ◽  
Distance Metrics ◽  
Phylogenetic Distance ◽  
Pandemic Preparedness ◽  
Competitive Fitness ◽  
Viral Neutralization ◽  
Genomic Signatures ◽  
Genome Wide ◽  
Geographical Regions ◽  
Over Time

Highly transmissible or immuno-evasive SARS-CoV-2 variants have intermittently emerged and outcompeted previously circulating strains, resulting in repeated COVID-19 surges, reinfections, and breakthrough infections in vaccinated individuals. With over 5 million SARS-CoV-2 genomes sequenced globally over the last 2 years, there is unprecedented data to decipher how competitive viral evolution results in the emergence of fitter SARS-CoV-2 variants. Much attention has been directed to studying how specific mutations in the Spike protein impact its binding to the ACE2 receptor or viral neutralization by antibodies, but there is limited knowledge of genomic signatures shared primarily by dominant variants. Here we introduce a methodology to quantify the genome-wide distinctiveness of polynucleotide fragments of various lengths (3- to 240-mers) that constitute SARS-CoV-2 lineage genomes. Compared to standard phylogenetic distance metrics and overall mutational load, the quantification of distinctive 9-mer polynucleotides provides a higher resolution of separation between variants of concern (Reference = 89, IQR: 65-108; Alpha = 166, IQR: 150-182; Beta 130, IQR: 113-147; Gamma = 165, IQR: 152-180; Delta = 234, IQR: 216-253; and Omicron = 294, IQR: 287-315). The similar scoring of the Alpha and Gamma variants by our methodology is consistent with these strains emerging at approximately the same time and circulating in distinct geographical regions as dominant strains. Furthermore, evaluation of genomic distinctiveness for 1,363 lineages annotated in GISAID highlights that polynucleotide diversity has increased over time (R2 = 0.37) and that VOCs show high distinctiveness compared to non-VOC contemporary lineages. To facilitate similar real-time assessments on the competitive fitness potential of future variants, we are launching a freely accessible resource for infusing pandemic preparedness with genomic inference ("GENI" — https://academia.nferx.com/GENI). This study demonstrates the value of characterizing new SARS-CoV-2 variants by their genome-wide polynucleotide distinctiveness and emphasizes the need to go beyond a narrow set of mutations at known functionally salient sites.

scholarly journals Is there an imbalance in the supply and demand for universal accessibility knowledge? Twenty years of UAIS papers viewed through the lens of WCAG

2021 ◽  
Author(s):  
Frode Eika Sandnes
Keyword(s):  
Latin America ◽  
North America ◽  
Supply And Demand ◽  
Research Focus ◽  
Universal Accessibility ◽  
Geographical Regions ◽  
Research Profile ◽  
The Impact ◽  
Over Time

AbstractPurpose: Some universal accessibility practitioners have voiced that they experience a mismatch in the research focus and the need for knowledge within specialized problem domains. This study thus set out to identify the balance of research into the main areas of accessibility, the impact of this research, and how the research profile varies over time and across geographical regions. Method: All UAIS papers indexed in Scopus were analysed using bibliometric methods. The WCAG taxonomy of accessibility was used for the analysis, namely perceivable, operable, and understandable. Results: The results confirm the expectation that research into visual impairment has received more attention than papers addressing operable and understandable. Although papers focussing on understandable made up the smallest group, papers in this group attracted more citations. Funded research attracted fewer citations than research without funding. The breakdown of research efforts appears consistent over time and across different geographical regions. Researchers in Europe and North America have been active throughout the last two decades, while Southeast Asia, Latin America, and Middle East became active in during the last five years. There is also seemingly a growing trend of out-of-scope papers. Conclusions: Based on the findings, several recommendations are proposed to the UAIS editorial board.

scholarly journals Genetic Diversity of Near Genome-Wide Hepatitis C Virus Sequences during Chronic Infection: Evidence for Protein Structural Conservation Over Time

PLoS ONE ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. e19562 ◽  
Author(s):  
Hui Li ◽  
Austin L. Hughes ◽  
Nazneen Bano ◽  
Susan McArdle ◽  
Stephen Livingston ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Chronic Infection ◽  
Genome Wide ◽  
Structural Conservation ◽  
Over Time

scholarly journals Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Juhye M Lee ◽  
Rachel Eguia ◽  
Seth J Zost ◽  
Saket Choudhary ◽  
Patrick C Wilson ◽  
...  
Keyword(s):  
Influenza Virus ◽  
Viral Evolution ◽  
Surface Protein ◽  
Viral Escape ◽  
Viral Neutralization ◽  
Influenza Hemagglutinin ◽  
Human Sera ◽  
Order Of Magnitude ◽  
Amino Acid Mutations ◽  
Major Surface

A longstanding question is how influenza virus evolves to escape human immunity, which is polyclonal and can target many distinct epitopes. Here, we map how all amino-acid mutations to influenza’s major surface protein affect viral neutralization by polyclonal human sera. The serum of some individuals is so focused that it selects single mutations that reduce viral neutralization by over an order of magnitude. However, different viral mutations escape the sera of different individuals. This individual-to-individual variation in viral escape mutations is not present among ferrets that have been infected just once with a defined viral strain. Our results show how different single mutations help influenza virus escape the immunity of different members of the human population, a phenomenon that could shape viral evolution and disease susceptibility.

scholarly journals Predicting context specific enhancer-promoter interactions from ChIP-Seq time course data

2017 ◽  
Author(s):  
Tomasz Dzida ◽  
Mudassar Iqbal ◽  
Iryna Charapitsa ◽  
George Reid ◽  
Henk Stunnenberg ◽  
...  
Keyword(s):  
Estrogen Receptor Alpha ◽  
Time Course ◽  
Target Genes ◽  
Mcf7 Cells ◽  
Genome Wide ◽  
A Genome ◽  
Machine Learning Approach ◽  
Protein Occupancy ◽  
Context Specific ◽  
Over Time

We have developed a machine learning approach to predict context specific enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.

scholarly journals Genome-Wide Surveillance of Genital Herpes Simplex Virus Type 1 From Multiple Anatomic Sites Over Time

2018 ◽  
Vol 218 (4) ◽  
pp. 595-605 ◽  
Author(s):  
Mackenzie M Shipley ◽  
Daniel W Renner ◽  
Mariliis Ott ◽  
David C Bloom ◽  
David M Koelle ◽  
...  
Keyword(s):  
Herpes Simplex Virus ◽  
Herpes Simplex ◽  
Genital Herpes ◽  
Virus Type ◽  
Herpes Simplex Virus Type ◽  
Genome Wide ◽  
Simplex Virus ◽  
Over Time

Abstract 439: Trajectory Analysis of Left Ventricular Dimensions From Biobank Data Uncovers Novel Genetic Associations

2020 ◽  
Vol 127 (Suppl_1) ◽  
Author(s):  
Tess Pottinger ◽  
Megan J Puckelwartz ◽  
Lorenzo L Pesce ◽  
Anthony Gacita ◽  
Isabella Salamone ◽  
...  
Keyword(s):  
Heart Failure ◽  
Longitudinal Data ◽  
Association Studies ◽  
The United States ◽  
Left Ventricular ◽  
Genome Wide Association Studies ◽  
Qtc Interval ◽  
Regulatory Regions ◽  
Genome Wide ◽  
Over Time

Background: Approximately 6 million adults in the United States have heart failure. The progression of heart failure is variable arising from differences in sex, age, genetic background including ancestry, and medication response. Many population-based genetic studies of heart failure have been cross-sectional in nature, failing to gain additional power from longitudinal analyses. As heart failure is known to change over time, using longitudinal data trajectories as a quantitative trait will increase power in genome wide association studies (GWAS). Methods: We used the electronic health record in a racially and ethnically diverse medical biobank from a single, metropolitan US center. We used whole genome data from 896 unrelated participants analyzed, including 494 who had at least 1 electrocardiogram and 324 who had more than 1 echocardiogram (average of 3 observations per person). A mixture model based semiparametric latent growth curve model was used to cluster outcome measures used for genome-wide analyses. Results: GWAS on the trajectory probability of QTc interval identified significant associations with variants in regulatory regions proximal to the WLS gene, which encodes Wntless, a Wnt ligand secretion mediator. WLS was previously associated with QTc and myocardial infarction, thus confirming the power of the method. GWAS on the trajectory probability of left ventricular diameter (LVIDd) identified significant associations with variants in regulatory regions near MYO10 , which encodes unconventional Myosin-10. MYO10 was previously associated with obesity and metabolic syndrome. Conclusions: This is the first study to show an association with variants in or near MYO10 and left ventricular dimension changes over time. Further, we found that using trajectory probabilities can provide increased power to find novel associations with longitudinal data. This reduces the need for larger cohorts, and increases yield from smaller, well-phenotyped cohorts, such as those found in biobanks. This approach should be useful in the study of rare diseases and underrepresented populations.

scholarly journals Posttraumatic psychopathology and the pace of the epigenetic clock: a longitudinal investigation

2018 ◽  
Vol 49 (5) ◽  
pp. 791-800 ◽  
Author(s):  
Erika J. Wolf ◽  
Mark W. Logue ◽  
Filomene G. Morrison ◽  
Elizabeth S. Wilcox ◽  
Annjanette Stone ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Alcohol Use ◽  
Psychiatric Symptoms ◽  
Alcohol Use Disorders ◽  
Cellular Aging ◽  
Epigenetic Clock ◽  
Afghanistan War ◽  
Genome Wide ◽  
Dna Methylation Age ◽  
Over Time

AbstractBackgroundPosttraumatic stress disorder (PTSD) and stress/trauma exposure are cross-sectionally associated with advanced DNA methylation age relative to chronological age. However, longitudinal inquiry and examination of associations between advanced DNA methylation age and a broader range of psychiatric disorders is lacking. The aim of this study was to examine if PTSD, depression, generalized anxiety, and alcohol-use disorders predicted acceleration of DNA methylation age over time (i.e. an increasing pace, or rate of advancement, of the epigenetic clock).MethodsGenome-wide DNA methylation and a comprehensive set of psychiatric symptoms and diagnoses were assessed in 179 Iraq/Afghanistan war veterans who completed two assessments over the course of approximately 2 years. Two DNA methylation age indices (Horvath and Hannum), each a weighted index of an array of genome-wide DNA methylation probes, were quantified. The pace of the epigenetic clock was operationalized as change in DNA methylation age as a function of time between assessments.ResultsAnalyses revealed that alcohol-use disorders (p = 0.001) and PTSD avoidance and numbing symptoms (p = 0.02) at Time 1 were associated with an increasing pace of the epigenetic clock over time, per the Horvath (but not the Hannum) index of cellular aging.ConclusionsThis is the first study to suggest that posttraumatic psychopathology is longitudinally associated with a quickened pace of the epigenetic clock. Results raise the possibility that accelerated cellular aging is a common biological consequence of stress-related psychopathology, which carries implications for identifying mechanisms of stress-related cellular aging and developing interventions to slow its pace.

scholarly journals WordSeeker: concurrent bioinformatics software for discovering genome-wide patterns and word-based genomic signatures

2010 ◽  
Vol 11 (S12) ◽  
Author(s):  
Jens Lichtenberg ◽  
Kyle Kurz ◽  
Xiaoyu Liang ◽  
Rami Al-ouran ◽  
Lev Neiman ◽  
...  
Keyword(s):  
Genomic Signatures ◽  
Genome Wide ◽  
Bioinformatics Software

scholarly journals Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

Archaea ◽  
2008 ◽  
Vol 2 (3) ◽  
pp. 159-167 ◽  
Author(s):  
Betsey Dexter Dyer ◽  
Michael J. Kahn ◽  
Mark D. LeBlanc
Keyword(s):  
Environmental Conditions ◽  
Convergent Evolution ◽  
Regression Tree ◽  
Classification And Regression Tree ◽  
Evolutionary Divergence ◽  
Cart Analysis ◽  
Genomic Signatures ◽  
Genome Wide ◽  
Classification And Regression ◽  
Temperature Optima

Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results.

scholarly journals Genome-wide alignment-free phylogenetic distance estimation under a no strand-bias model

2021 ◽  
Author(s):  
Metin Balaban ◽  
Nishat Anjum Bristy ◽  
Ahnaf Faisal ◽  
Md Shamsuzzoha Bayzid ◽  
Siavash Mirarab
Keyword(s):  
Dna Sequences ◽  
Distance Estimation ◽  
Sequence Evolution ◽  
Phylogenetic Distance ◽  
Strand Bias ◽  
Alignment Free ◽  
Bias Model ◽  
Genome Wide ◽  
Genome Wide Data ◽  
Complex Models

While aligning sequences has been the dominant approach for determining homology prior to phylogenetic inference, alignment-free methods have much appeal in terms of simplifying the process of inference, especially when analyzing genome-wide data. Furthermore, alignment-free methods present the only option for some emerging forms of data such as genome skims, which cannot be assembled. Despite the appeal, alignment-free methods have not been competitive with alignment-based methods in terms of accuracy. One limitation of alignment-free methods is that they typically rely on simplified models of sequence evolution such as Jukes-Cantor. It is possible to compute pairwise distances under more complex models by computing frequencies of base substitutions provided that these quantities can be estimated in the alignment-free setting. A particular limitation is that for many forms of genome-wide data, which arguably present the best use case for alignment-free methods, the strand of DNA sequences is unknown. Under such conditions, the so-called no-strand bias models are the most complex models that can be used. Here, we show how to calculate distances under a no-strain bias restriction of the General Time Reversible (GTR) model called TK4 without relying on alignments. The method relies on replacing letters in the input sequences, and subsequent computation of Jaccard indices between k-mer sets. For the method to work on large genomes, we also need to compute the number of k-mer mismatches after replacement due to random chance. We show in simulation that these alignment-free distances can be highly accurate when genomes evolve under the assumed models, and we examine the effectiveness of the method on real genomic data.

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